Introduction to Multi-level Models

1 Introduction to multi-level models for correlated data

For more, see:

• David Rocke’s materials from the 2021 edition of this course
  • May 25 - June 1 lectures
• Other UC Davis courses:
  • EVE 225: “Linear Mixed Modeling in Ecology & Evolution”
    • usually taught every other winter or spring by Kate Laskowski
    • materials, including syllabus and lecture videos: https://laskowskilab.faculty.ucdavis.edu/teaching-2/
  • STA/BST 224: “Analysis of Longitudinal Data”
    • usually taught every spring by Shuai Chen
    • should be accessible after completing Epi 204
  • EPI 226 “Methods for Longitudinal & Repeated Measurement Data”
    • usually taught by Heejung Bang
  • PSC 205D “Multilevel Models”
  • PSC 205G “Applied Longitudinal Data Analysis”
  • STA 101 “Advanced Applied Statistics for the Biological Sciences”
  • STA 207 “Statistical Methods for Research II”
  • STA 232B “Applied Statistics II”
    • usually taught every winter by Jiming Jiang
  • PLS 207: “Applied Statistical Modeling for the Environmental Sciences”
  • EDU 236: “Application of Hierarchical Linear Models in Education Research”
  • HDE 205: “Longitudinal Data Analysis”
• Books:
  • Dobson and Barnett (2018) Chapter 11
  • Vittinghoff et al. (2012) Chapter 7
  • Gelman and Hill (2007)
  • Jiang and Nguyen (2021)
    • by UC Davis Statistics Professor and GGE faculty member Jiming Jiang
  • Faraway (2016)
  • McCulloch, Searle, and Neuhaus (2008)
  • Hedeker and Gibbons (2006)
  • Wakefield (2013)
  • Zuur (2009)
  • Diggle et al. (2013)
  • Fitzmaurice, Laird, and Ware (2012)
  • Fitzmaurice et al. (2009)
  • Gałecki and Burzykowski (2013)
  • Congdon (2020)
  • Molenberghs and Verbeke (2005)
  • Verbeke and Molenberghs (2000)
  • Jewell and Hubbard (2016)
    • by UC Berkeley professors

References

Congdon, Peter D. 2020. Bayesian Hierarchical Models: With Applications Using R, Second Edition. 2nd edition. Milton: CRC Press.

Diggle, Peter, Scott Zeger, Patrick Heagerty, and Kung-Yee Liang. 2013. Analysis of Longitudinal Data. Second edition. Vol. 25. Oxford Statistical Science Series. United Kingdom: Oxford University Press.

Dobson, Annette J, and Adrian G Barnett. 2018. An Introduction to Generalized Linear Models. 4th ed. CRC press. https://doi.org/10.1201/9781315182780.

Faraway, Julian J. 2016. Extending the Linear Model with r: Generalized Linear, Mixed Effects and Nonparametric Regression Models. 2nd ed. Chapman; Hall/CRC. https://doi.org/10.1201/9781315382722.

Fitzmaurice, Garrett M, Marie Davidian, Geert Verbeke, and Geert Molenberghs. 2009. Longitudinal Data Analysis. Chapman & Hall/CRC Handbooks of Modern Statistical Methods. Boca Raton: CRC Press. https://doi.org/10.1201/9781420011579.

Fitzmaurice, Garrett M, Nan M Laird, and James H Ware. 2012. Applied Longitudinal Analysis. 2nd ed. Vol. 998. Wiley Series in Probability and Statistics. Chicester: Wiley. https://doi.org/10.1002/9781119513469.

Gałecki, Andrzej T., and Tomasz. Burzykowski. 2013. Linear Mixed-Effects Models Using R : A Step-by-Step Approach. Springer Texts in Statistics. New York, NY: Springer. https://doi.org/10.1007/978-1-4614-3900-4.

Gelman, Andrew, and Jennifer Hill. 2007. Data Analysis Using Regression and Multilevel/Hierarchical Models. Analytical Methods for Social Research. Cambridge, MA: Cambridge University Press.

Hedeker, Donald R., and Robert D. Gibbons. 2006. Longitudinal Data Analysis. Wiley Series in Probability and Statistics. Hoboken, N.J: Wiley-Interscience.

Jewell, Nicholas P, and Alan E Hubbard. 2016. Analysis of Longitudinal Studies in Epidemiology. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis. https://books.google.com/books?id=-LoLPQAACAAJ.

Jiang, Jiming, and Thuan Nguyen. 2021. Linear and Generalized Linear Mixed Models and Their Applications. Second edition. Springer Series in Statistics. New York, NY: Springer. https://doi.org/10.1007/978-1-0716-1282-8.

McCulloch, Charles E, Searle Shayle R, and John M Neuhaus. 2008. Generalized, Linear, and Mixed Models. 2nd ed. Vol. 651. John Wiley & Sons.

Molenberghs, Geert., and Geert. Verbeke. 2005. Models for Discrete Longitudinal Data. Springer Series in Statistics. New York: Springer Science+Business Media, Inc. https://doi.org/10.1007/0-387-28980-1.

Verbeke, Geert, and Geert Molenberghs. 2000. Linear Mixed Models for Longitudinal Data. 1st ed. Springer Series in Statistics. New York, NY: SpringerLink (Online service); Springer. https://doi.org/10.1007/978-1-4419-0300-6.

Vittinghoff, Eric, David V Glidden, Stephen C Shiboski, and Charles E McCulloch. 2012. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. 2nd ed. Springer. https://doi.org/10.1007/978-1-4614-1353-0.

Wakefield, Jon. 2013. Bayesian and Frequentist Regression Methods. 1st ed. 2013. Springer Series in Statistics. New York, NY: Springer New York.

Zuur, Alain F. 2009. Mixed Effects Models and Extensions in Ecology with r. Statistics for Biology and Health. New York ; Springer.